E3S Web Conf.
Volume 244, 2021XXII International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies (EMMFT-2020)
|Number of page(s)||11|
|Section||Environmental and Climate Technologies|
|Published online||19 March 2021|
Non-visual platform components for a system of polyvariant calculation of dynamic models of the production process
1 Agrophysical Research Institute, Grazhdansky pr., 14, St. Petersburg, 195220, Russia
2 Peter the Great St.Petersburg Polytechnic University, Polytechnicheskaya, 29, St. Petersburg, 195251, Russia
3 Moscow State University of Civil Engineering, 26, Yaroslavskoye shosse, Moscow, 129337, Russia
* Corresponding author: email@example.com
Production process models have been used for many years in decision support systems in agriculture. They allow solving the problems of forecasting the yield, operational support, integration with GIS, calculating pedotransfer functions, etc. A high-performance, efficient platform has been developed to create powerful yet lightweight applications for a wide range of tasks. These tasks were solved in the RW.Ring platform, which was developed specifically for the new version of the APEX polyvariant calculation system instead of the outdated kernel of the old system, which contained many non-optimal solutions that impede the effective development of the system. While the new version of the polyvariant calculation system itself is currently under development, the platform itself already contains debugged working modules and can be used for a large number of similar applications.The platform’s performance is confirmed by the successful development of the Schicksal statistical analysis program. In the future, the platform will develop in parallel with the new version of the APEX polyvariant analysis system, as well as other programs based on it. The RW.Ring platform can be recommended as a set of standard libraries designed for building any shells for a large number of models.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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